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Users requested batched operation for
cwt
in #445. This can be done by adding anaxis
argument as in this PR. This PR allows the input data to be n-dimensional with batched operation over all axes aside from the specified cwtaxis
. For 1D data, the behavior is unchanged from before.The final shape of the output for n-dimensional
data
becomes:(len(scales),) + data.shape
(i.e. the scales dimension is always first as it was for the 1D case previously)For the
'conv'
case implementation is via a simple for loop, but for the'fft'
case we do not have to repeat the FFT of the wavelet filter for each item in the batch, so there is a performance benefit to batched operation.a subset of benchmark results.
first, for non-batch cases
a few batch (n_batch=5) cases
Summary for the 2048/shan/float32 case:
closes #445